Application of cascade-correlation neural networks to nonlinear system identification
| dc.contributor.author | Mueller, Klaus C. | en |
| dc.contributor.department | Electrical Engineering | en |
| dc.date.accessioned | 2022-11-09T06:28:00Z | en |
| dc.date.available | 2022-11-09T06:28:00Z | en |
| dc.date.issued | 1994 | en |
| dc.description.abstract | Much research in recent years has been done in applying artificial neural networks to the problem of nonlinear system identification. The most common neural network architecture, the multilayer feed-forward network, trained with the backpropagation algorithm, has been shown to be capable of universal function approximation which makes it applicable to a much wider range of problems than other nonlinear identification techniques. While these neural networks show great potential, they still suffer several drawbacks, such as slow convergence toward a solution. New neural network architectures have been proposed in an attempt to overcome these limitations. This study examines one such architecture, Cascade-Correlation, and its usefulness in system identification applications, particularly the nonlinear case. | en |
| dc.description.degree | M.S. | en |
| dc.format.extent | vi, 114 leaves | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.uri | http://hdl.handle.net/10919/112536 | en |
| dc.language.iso | en | en |
| dc.publisher | Virginia Polytechnic Institute and State University | en |
| dc.relation.isformatof | OCLC# 32290680 | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject.lcc | LD5655.V855 1994.M845 | en |
| dc.subject.lcsh | Neural networks (Computer science) | en |
| dc.subject.lcsh | Nonlinear theories | en |
| dc.subject.lcsh | System identification | en |
| dc.title | Application of cascade-correlation neural networks to nonlinear system identification | en |
| dc.type | Thesis | en |
| dc.type.dcmitype | Text | en |
| thesis.degree.discipline | Electrical Engineering | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | M.S. | en |
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